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Author*The author of this computation has been verified*
R Software Modulerwasp_pairs.wasp
Title produced by softwareKendall tau Correlation Matrix
Date of computationFri, 11 Dec 2015 09:45:49 +0000
Cite this page as followsStatistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?v=date/2015/Dec/11/t14498275177q6omcqb4bwyuk9.htm/, Retrieved Thu, 16 May 2024 08:14:40 +0000
Statistical Computations at FreeStatistics.org, Office for Research Development and Education, URL https://freestatistics.org/blog/index.php?pk=285863, Retrieved Thu, 16 May 2024 08:14:40 +0000
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Original text written by user:
IsPrivate?No (this computation is public)
User-defined keywords
Estimated Impact109
Family? (F = Feedback message, R = changed R code, M = changed R Module, P = changed Parameters, D = changed Data)
-       [Kendall tau Correlation Matrix] [Correlatie toesch...] [2015-12-11 09:45:49] [08ad43dc796ab34076e7be4bfcaa9e56] [Current]
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Dataseries X:
2441 14.81
3406 47.61
4029 42.06
1924 6.87
2319 21.85
2156 33.19
2117 12.28
2189 6.78
2625 8.91
1959 15.18
3096 8
1997 10.14
1813 13.63
2648 8.45
2648 13.81
5782 68.09
2218 15.89
25289 54.81
25389 57.43
25196 61.92
24153 61.03
26079 52.32
26540 54.59
25099 68.24
27402 117.12
26206 61.75
26526 53.31
27154 74.69
24464 59.7
24967 55.18
24713 84.84
26733 54.8
24578 54.1
26092 59.57
24486 48.04
24630 54.8
26233 53.45
26492 51.31
24973 47.95
27437 109.26
23829 57.06
27158 83.23
25670 49.17
23530 47.61
24474 74.36
26668 49.62
26060 63.02
24856 54.98
24067 50.08
25545 56.35
24213 55.98
23703 54.62
23566 46.5
22876 66.01
22744 51.51
27615 105.87
24421 62.5
24728 49.89
25732 54.03
24204 52.6
23869 48.09
24120 51.56
22474 54.07
26406 90.85
22440 47.81
20387 46.5
21609 62.5
24905 105.87
21584 49.89
20920 51.51
5042 31.01
4353 17.58
7996 79.89
3998 24.69
4697 47.61
7837 37.46
3512 17.95
3503 16.87
3572 20.2
3918 22.34
4767 16.08
5833 61.03
4154 22.47
3894 15.09
4133 17.36
4273 17.57
5574 24.52
5029 16.37
5279 30.22
4876 41.56
3850 16.82
4109 20.65
4137 22.18
3725 23.55
5675 55.98
3405 14.81
3568 15.24
3408 22
7203 76.46
5392 15.15
4053 17.28
7863 50.43
3716 24.26
4027 18.51
3608 15.8
3333 19.55
3014 22.06
5014 73.86
4328 53.05
2956 17.88
6535 58.84
3153 20.59
3081 34
2996 22.61
3150 16.49
3673 25.16
2870 11.02
3230 14.35
3821 55.18
3178 16.62
2988 9.24
2347 41.76
2891 11.72
4775 31.61
4758 74.04
2962 11.73
2687 18.84
2825 18.67
4201 10.23
2545 17.95
2626 11.51
3556 15.81
6069 71.18
2795 11.49
2763 8.87
3024 15.98
2622 15.09
3800 38.9
5217 28.75
3163 8.16
3765 8.86
2991 13.63
4856 7.37
5752 52.32
3351 13.76
3392 9.24
3145 8.65
3820 22.3
4790 42.49
2729 15.24
3025 10.57
2428 33.62
2981 14.06
3051 7.21
6330 68.52
3006 15.61
3301 16.32
5265 48.04
3975 8.43
2643 6.87
3130 12.71
3832 22.28
3819 8.88
3037 9.34
4272 14.24
10589 61.75
8945 48.33
7764 23.19
8704 31.73
7546 18.67
7694 17.59
10499 80.61
7614 18.3
8248 24.52
8158 15.81
8174 25.41
8097 18.08
9154 18.29
10287 38.18
7972 23.06
7518 20.92
9492 16.8
8317 16.32
8158 17.9
9174 31.3
8262 23.26
10533 77.54
10434 51.51
8047 24.63
7831 24.26
8062 15.89
8834 42.64
8957 23.08
8753 21.73
7663 16.23
8290 18.36
8435 19.59
10802 57.06
9391 17.45
10280 59.82
8461 16.78
9152 17.06
8380 23.59
8171 15.47
8386 23.04
8212 22.02
9103 18.86
8461 16.78
8443 21.57
9253 34.98
8220 20.53
10435 74.84
8627 31.47
8196 20.48
9431 54.03
7917 34.98
8186 59.82
4350 21.57
9341 29.22
9545 29.18
10624 54.82
10665 24.57
11698 44.67
9516 24.08
8815 29.55
8389 24.79
10475 23.29
10170 31.9
9192 22.3
9198 31.01
8764 25.16
9996 24.78
9219 31.73
10801 87.1
8631 27.41
11110 68.24
8101 29.68
9696 24.32
10542 23.41
10069 30.59
11789 63.02
9416 22.28
9543 48.6
8919 23.86
8958 22.19
8933 30.22
11251 83.5
9589 31.3
8870 21.85
9108 25.55
9544 29.04
9611 27.69
11798 57.47
11269 25.53
10411 32.06
9690 25.25
9625 31.51
9522 30.49
10330 31.47
10803 68.29
9946 29
9782 43.45
11660 83.31
9960 23.94
10286 28.95
10790 62.5
10188 27.33
9465 83.31
7791 27.33
7793 28.95
8175 23.94
10328 62.5
4510 12.62
3589 9.25
4039 16.23
7656 15.15
4662 8.34
5001 33.53
7089 10.48
4103 13.97
4314 8.79
7187 68.43
5954 42.4
3597 14.15
3647 15.52
8287 47.95
4192 7.21
4046 6.78
5195 22.19
7626 67.31
5232 14.49
5251 23.94
5043 11.33
5842 52.29
4879 9.25
5429 9.53
4772 27.45
6159 12.95
3761 15.51
8832 46.5
4337 15.47
3979 14.04
4886 13
6057 16.06
4922 23.94
4650 11.33
4938 12.95
6610 46.5
6041 67.31
11379 72.17
10702 53.31
7455 16.08
8425 7.37
7679 9.85
8312 10.23
7238 9.15
9412 16.8
7698 9.86
7776 14.75
7870 16.97
8122 9.64
9138 39.89
10187 29.74
8315 23.29
8424 14.62
7731 12.48
8079 11.7
7926 8
9975 49.17
8397 8.43
8572 15.19
8157 10.01
7856 10.47
9835 43.62
9524 17.45
7750 16.37
8221 23.41
8998 34.75
9875 69.65
8015 8.34
7749 13.84
8174 15.37
8504 16.74
11129 17.1
12615 48.09
12219 12.92
10828 10.84
11463 17.65
12524 68.9
10638 16.08
11085 25.53
10831 15.63
12022 53.88
10544 14.59
11569 17.06
10889 9.53
11064 29.04
11221 14.54
10339 17.65
10652 14.59
11155 17.1
3597 9.86
2768 18.47
2812 11.73
3781 41.39
7789 31.24
2886 11.35
2283 16.12
2389 13.98
3784 54.81
2990 17.58
3615 16.25
2767 8.87
2673 11.14
3068 24.79
2894 10.65
2621 18.3
6440 73.67
3082 35.66
5532 70.56
2421 10.92
3653 16.28
2656 18.36
3059 17.28
3341 50.08
2387 9.34
2469 12.61
2758 24.32
2254 14.75
2305 9.25
7075 44.53
2260 17.65
2988 10.47
2091 16.1
2169 8.91
15711 47.67
14409 47.8
17306 41.38
17157 40.68
17611 46.15
20394 103.7
18757 39.89
20250 84.84
17622 46.28
17270 41.17
18330 54.82
17580 48.33
18128 44.01
17261 41.39
17287 47.61
17433 48.5
17518 38.9
16890 41.76
18728 61.27
16953 42.64
17970 74.36
16920 34.75
19400 68.81
15769 35.2
17431 39.03
16058 40.56
15312 35.66
16214 36.89
15962 41.56
15852 33.62
15634 33.19
17699 40.38
16100 48.6
16252 33.53
17874 94.84
14058 34
14466 43.45
14531 34.98
14102 33.55
14014 28.76
16871 29.04
14903 32.51
16411 86.82
14687 35.02
14363 32.46
16062 30.84
15361 66.01
16134 71.8
14256 27.45
15863 71.8
14196 33.55
14120 34.98
14825 35.02
16946 30.84
23867 80.78
24107 74.04
24041 73.45
24415 78.56
24496 87.1
24022 78.43
24367 93.55
23869 73.67
24495 72.17
23818 71.18
24081 79.89
24132 103.7
23651 72.96
23622 73.66
23726 80.61
23942 76.29
24573 117.12
23085 83.5
22612 68.43
22960 75.46
22921 76.46
23510 69.65
22729 76.83
23047 75.28
22850 68.09
23426 94.84
22812 73.93
22446 70.56
23567 103.71
23185 71.79
22777 77.54
23508 109.26
23193 68.52
23006 70.1
22332 72.37
22347 74.88
23061 111.66
22887 83.31
22890 74.84
22701 73.41
22467 75.43
22357 68.62
22443 67.31
22824 72.32
22906 105.87
23059 70.7
23055 68.9
22564 86.82
18570 72.32
20329 105.87
19279 67.31
19541 83.31
19517 70.7
6519 15.54
7169 14.75
8107 16.25
10668 59.7
6650 22.47
5726 13.76
5224 16.03
6297 29.68
5011 21.01
5075 18.87
5434 23.19
11758 78.56
4531 23.36
5373 16.62
6343 46.28
20051 36.13
5482 16.24
5066 15.82
5040 19.65
5100 14.15
4679 22.55
10940 54.98
6035 13.81
5364 15.37
4424 14.24
4486 21
4962 29.22
10445 75.46
5973 16.28
5415 23.26
17792 49.43
5581 22.18
4997 17.51
6893 40.56
10181 52.6
7007 21.57
6621 19.1
7309 15.63
6114 14.04
5521 21.61
5263 30.04
5400 17.43
6141 15.35
5736 33.55
16104 58.39
10810 73.41
5057 19.05
5732 22.16
4000 21.57
4000 33.55
4200 58.39
3551 21.09
4025 25.41
5591 16.97
3868 18.84
3566 23.36
4525 48.5
3752 18.46
3182 23.23
6152 80.78
3548 18.47
6876 61.92
3199 24.69
3386 15.98
3411 18.25
6892 38.35
4920 31.9
3193 17.76
3054 15.18
3262 22.37
3509 21.02
3471 15.52
3101 17.65
5956 50.8
6232 56.35
5456 16.74
3186 18.88
3751 41.93
2973 17.19
5548 30.59
3219 22.55
6595 76.83
4886 24.63
3082 23.55
3516 15.61
3807 21.07
3607 19.45
3163 22.61
4981 60.41
3276 22.16
3278 21.12
3850 35.57
3439 16.06
5545 54.62
4749 32.06
3656 23.59
3520 17.37
4392 17.65
3057 23.63
6542 75.43
2785 21.12
3057 23.63
4379 17.65
23934 31.61
23625 31.23
26185 74.69
23777 36
24586 38.18
25439 29.74
24037 38.35
25403 36.13
25133 61.27
24023 31.02
23901 30.53
24892 44.67
24560 33.86
24226 31.24
24885 37.46
25466 93.55
24903 28.75
23761 49.25
23868 42.4
26118 103.71
25120 44.53
26119 49.43
25440 50.43
24206 45.76
25312 57.47
24499 42.49
24330 44.07
24217 42.06
25047 47.9
25817 68.81
25466 51.51
25410 50.8
26246 43.62
25718 83.23
26543 55.68
26723 58.39
26700 53.88
24743 57.35
25520 71.8
25298 57.3
26382 90.85
25719 59.82
24547 53.6
25640 60.41
26103 111.66
24911 52.29
25199 59.86
25308 68.29
17000 58.39
12000 59.82
20000 71.8
3915 20.2
3229 18.87
6671 44.01
5937 33.86
3639 13.76
4274 27.41
3781 20.92
5612 76.29
4498 12.48
3520 21.09
6323 57.43
3622 11.49
4085 14.35
3978 13.97
3788 13.27
3973 18.74
3268 13.98
6852 17.43
6237 12.64
9194 70.7
9177 30.84
6170 16.34
6295 27.33
5878 16.39
7172 55.68
5741 11.33
7093 12.92
5774 19.45
5690 18.9
7717 49.89
6511 18.86
6989 49.89
9006 70.7
6052 11.33
5094 16.34
6198 27.33
8845 30.84
6219 11.13
5984 8.86
7303 24.78
6887 18.29
8083 13.97
18978 73.66
25222 54.8
6093 17.57
7206 16.24
8070 41.38
16129 31.23
7646 10.64
5415 16.11
10480 9.85
5998 11.35
6289 18.46
6146 11.72
12308 73.93
7128 14.75
7653 21.73
10130 47.9
8741 12.71
7719 15.98
8167 13.84
7786 27.69
8091 14.29
8089 12.62
7219 19.65
7373 21.02
20659 53.45
7158 20.65
7503 12.28
7654 39.03
7747 19.47
8631 29
6867 18.01
17989 51.56
6798 20.53
7485 14.59
7085 13
7235 20.57
8534 72.37
7785 57.35
7017 14.31
5951 19.1
6709 32.51
6999 21.12
6175 16.39
5927 20.57
6703 14.59
6118 21.12
4565 8.16
6178 30.53
5389 10.64
5079 10.43
7382 72.96
4305 13.27
4216 10.65
7849 54.1
4248 15.54
4238 17.76
4746 40.68
4227 11.02
4946 24.08
4234 15.41
4379 17.59
5464 9.15
4240 16.87
5465 8.79
5634 44.07
3984 17.19
6957 49.62
4492 12.15
3863 8.45
3845 8.88
3768 15.64
6071 70.1
3794 15.82
4078 17.9
3927 10.92
3931 16.82
5368 10.01
5142 35.2
5165 23.86
4432 14.29
5082 16.78
6087 53.6
4434 15.35
4360 17.37
5634 14.31
7836 47.81
5394 14.26
4327 15.8
4142 12.64
5251 25.25
4951 10.84
4565 9.25
4463 28.76
5922 68.62
4581 16.82
7566 31.02
5500 15.9
5745 18.08
6924 9.64
5354 11.14
5563 18.25
5369 17.36
5658 8.65
5215 11.51
5824 11.13
6667 24.57
7795 73.45
5490 10.43
5232 13.76
7739 54.59
5404 16.03
6045 41.17
6012 18.88
6287 36.89
5185 10.14
8080 71.79
7229 25.55
5602 19.59
5329 17.51
5401 18.51
8283 51.31
6359 11.7
5457 10.57
5654 17.33
6391 12.15
5765 15.98
6707 10.48
8214 45.76
5621 12.61
6387 32.46
8299 72.32
6526 12.95
5514 19.5
6659 28.95
6023 20.48
5701 19.05
6628 14.54
5845 21.07
5778 18.01
5668 20.52
5982 16.34
8294 51.51
5970 14.26
7440 57.3
5385 16.34
6226 28.95
6905 51.51
7566 72.32
6033 12.95
3338 21.01
2778 22.34
2876 13.63
3059 16.11
2827 15.41
3819 23.06
3319 18.74
5529 14.62
2791 16.49
6521 59.57
2959 15.9
4378 46.15
6042 36
3715 29.55
6219 78.43
2890 16.12
3134 23.23
3544 21
3915 23.08
3139 22
2989 17.33
2856 13.63
5619 40.38
3955 29.04
3027 16.1
3760 19.47
6323 49.25
3362 22.37
6263 54.8
5720 15.19
3035 14.06
6509 75.28
3123 15.64
3332 13.97
3298 15.51
4579 35.02
2963 20.52
5861 54.07
4549 18.9
6211 59.86
2942 16.82
3181 23.63
5019 17.1
6590 74.88
4528 31.51
3744 23.04
3096 21.61
2893 20.57
3946 17.1
2838 23.63
2804 20.57




Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net

\begin{tabular}{lllllllll}
\hline
Summary of computational transaction \tabularnewline
Raw Input & view raw input (R code)  \tabularnewline
Raw Output & view raw output of R engine  \tabularnewline
Computing time & 2 seconds \tabularnewline
R Server & 'Gwilym Jenkins' @ jenkins.wessa.net \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285863&T=0

[TABLE]
[ROW][C]Summary of computational transaction[/C][/ROW]
[ROW][C]Raw Input[/C][C]view raw input (R code) [/C][/ROW]
[ROW][C]Raw Output[/C][C]view raw output of R engine [/C][/ROW]
[ROW][C]Computing time[/C][C]2 seconds[/C][/ROW]
[ROW][C]R Server[/C][C]'Gwilym Jenkins' @ jenkins.wessa.net[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285863&T=0

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285863&T=0

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Summary of computational transaction
Raw Inputview raw input (R code)
Raw Outputview raw output of R engine
Computing time2 seconds
R Server'Gwilym Jenkins' @ jenkins.wessa.net







Correlations for all pairs of data series (method=pearson)
Toeschouwerssom_repcoef
Toeschouwers10.684
som_repcoef0.6841

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series (method=pearson) \tabularnewline
  & Toeschouwers & som_repcoef \tabularnewline
Toeschouwers & 1 & 0.684 \tabularnewline
som_repcoef & 0.684 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285863&T=1

[TABLE]
[ROW][C]Correlations for all pairs of data series (method=pearson)[/C][/ROW]
[ROW][C] [/C][C]Toeschouwers[/C][C]som_repcoef[/C][/ROW]
[ROW][C]Toeschouwers[/C][C]1[/C][C]0.684[/C][/ROW]
[ROW][C]som_repcoef[/C][C]0.684[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285863&T=1

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285863&T=1

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series (method=pearson)
Toeschouwerssom_repcoef
Toeschouwers10.684
som_repcoef0.6841







Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Toeschouwers;som_repcoef0.68380.64890.4542
p-value(0)(0)(0)

\begin{tabular}{lllllllll}
\hline
Correlations for all pairs of data series with p-values \tabularnewline
pair & Pearson r & Spearman rho & Kendall tau \tabularnewline
Toeschouwers;som_repcoef & 0.6838 & 0.6489 & 0.4542 \tabularnewline
p-value & (0) & (0) & (0) \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285863&T=2

[TABLE]
[ROW][C]Correlations for all pairs of data series with p-values[/C][/ROW]
[ROW][C]pair[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]Toeschouwers;som_repcoef[/C][C]0.6838[/C][C]0.6489[/C][C]0.4542[/C][/ROW]
[ROW][C]p-value[/C][C](0)[/C][C](0)[/C][C](0)[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285863&T=2

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285863&T=2

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Correlations for all pairs of data series with p-values
pairPearson rSpearman rhoKendall tau
Toeschouwers;som_repcoef0.68380.64890.4542
p-value(0)(0)(0)







Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111

\begin{tabular}{lllllllll}
\hline
Meta Analysis of Correlation Tests \tabularnewline
Number of significant by total number of Correlations \tabularnewline
Type I error & Pearson r & Spearman rho & Kendall tau \tabularnewline
0.01 & 1 & 1 & 1 \tabularnewline
0.02 & 1 & 1 & 1 \tabularnewline
0.03 & 1 & 1 & 1 \tabularnewline
0.04 & 1 & 1 & 1 \tabularnewline
0.05 & 1 & 1 & 1 \tabularnewline
0.06 & 1 & 1 & 1 \tabularnewline
0.07 & 1 & 1 & 1 \tabularnewline
0.08 & 1 & 1 & 1 \tabularnewline
0.09 & 1 & 1 & 1 \tabularnewline
0.1 & 1 & 1 & 1 \tabularnewline
\hline
\end{tabular}
%Source: https://freestatistics.org/blog/index.php?pk=285863&T=3

[TABLE]
[ROW][C]Meta Analysis of Correlation Tests[/C][/ROW]
[ROW][C]Number of significant by total number of Correlations[/C][/ROW]
[ROW][C]Type I error[/C][C]Pearson r[/C][C]Spearman rho[/C][C]Kendall tau[/C][/ROW]
[ROW][C]0.01[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.02[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.03[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.04[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.05[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.06[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.07[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.08[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.09[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[ROW][C]0.1[/C][C]1[/C][C]1[/C][C]1[/C][/ROW]
[/TABLE]
Source: https://freestatistics.org/blog/index.php?pk=285863&T=3

Globally Unique Identifier (entire table): ba.freestatistics.org/blog/index.php?pk=285863&T=3

As an alternative you can also use a QR Code:  

The GUIDs for individual cells are displayed in the table below:

Meta Analysis of Correlation Tests
Number of significant by total number of Correlations
Type I errorPearson rSpearman rhoKendall tau
0.01111
0.02111
0.03111
0.04111
0.05111
0.06111
0.07111
0.08111
0.09111
0.1111



Parameters (Session):
par1 = pearson ;
Parameters (R input):
par1 = pearson ;
R code (references can be found in the software module):
panel.tau <- function(x, y, digits=2, prefix='', cex.cor)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
rr <- cor.test(x, y, method=par1)
r <- round(rr$p.value,2)
txt <- format(c(r, 0.123456789), digits=digits)[1]
txt <- paste(prefix, txt, sep='')
if(missing(cex.cor)) cex <- 0.5/strwidth(txt)
text(0.5, 0.5, txt, cex = cex)
}
panel.hist <- function(x, ...)
{
usr <- par('usr'); on.exit(par(usr))
par(usr = c(usr[1:2], 0, 1.5) )
h <- hist(x, plot = FALSE)
breaks <- h$breaks; nB <- length(breaks)
y <- h$counts; y <- y/max(y)
rect(breaks[-nB], 0, breaks[-1], y, col='grey', ...)
}
x <- na.omit(x)
y <- t(na.omit(t(y)))
bitmap(file='test1.png')
pairs(t(y),diag.panel=panel.hist, upper.panel=panel.smooth, lower.panel=panel.tau, main=main)
dev.off()
load(file='createtable')
n <- length(y[,1])
n
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,paste('Correlations for all pairs of data series (method=',par1,')',sep=''),n+1,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,' ',header=TRUE)
for (i in 1:n) {
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
}
a<-table.row.end(a)
for (i in 1:n) {
a<-table.row.start(a)
a<-table.element(a,dimnames(t(x))[[2]][i],header=TRUE)
for (j in 1:n) {
r <- cor.test(y[i,],y[j,],method=par1)
a<-table.element(a,round(r$estimate,3))
}
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable.tab')
ncorrs <- (n*n -n)/2
mycorrs <- array(0, dim=c(10,3))
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Correlations for all pairs of data series with p-values',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'pair',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
cor.test(y[1,],y[2,],method=par1)
for (i in 1:(n-1))
{
for (j in (i+1):n)
{
a<-table.row.start(a)
dum <- paste(dimnames(t(x))[[2]][i],';',dimnames(t(x))[[2]][j],sep='')
a<-table.element(a,dum,header=TRUE)
rp <- cor.test(y[i,],y[j,],method='pearson')
a<-table.element(a,round(rp$estimate,4))
rs <- cor.test(y[i,],y[j,],method='spearman')
a<-table.element(a,round(rs$estimate,4))
rk <- cor.test(y[i,],y[j,],method='kendall')
a<-table.element(a,round(rk$estimate,4))
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'p-value',header=T)
a<-table.element(a,paste('(',round(rp$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rs$p.value,4),')',sep=''))
a<-table.element(a,paste('(',round(rk$p.value,4),')',sep=''))
a<-table.row.end(a)
for (iii in 1:10) {
iiid100 <- iii / 100
if (rp$p.value < iiid100) mycorrs[iii, 1] = mycorrs[iii, 1] + 1
if (rs$p.value < iiid100) mycorrs[iii, 2] = mycorrs[iii, 2] + 1
if (rk$p.value < iiid100) mycorrs[iii, 3] = mycorrs[iii, 3] + 1
}
}
}
a<-table.end(a)
table.save(a,file='mytable1.tab')
a<-table.start()
a<-table.row.start(a)
a<-table.element(a,'Meta Analysis of Correlation Tests',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Number of significant by total number of Correlations',4,TRUE)
a<-table.row.end(a)
a<-table.row.start(a)
a<-table.element(a,'Type I error',1,TRUE)
a<-table.element(a,'Pearson r',1,TRUE)
a<-table.element(a,'Spearman rho',1,TRUE)
a<-table.element(a,'Kendall tau',1,TRUE)
a<-table.row.end(a)
for (iii in 1:10) {
iiid100 <- iii / 100
a<-table.row.start(a)
a<-table.element(a,round(iiid100,2),header=T)
a<-table.element(a,round(mycorrs[iii,1]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,2]/ncorrs,2))
a<-table.element(a,round(mycorrs[iii,3]/ncorrs,2))
a<-table.row.end(a)
}
a<-table.end(a)
table.save(a,file='mytable2.tab')